DNA methylation GrimAge strongly predicts lifespan and healthspan

Ake T. Lu, Austin Quach, James G. Wilson, Alex P. Reiner, Abraham Aviv, Kenneth Raj, Lifang Hou, Andrea A. Baccarelli, Yun Li, James D. Stewart, Eric A. Whitsel, Themistocles L. Assimes, Luigi Ferrucci, Steve Horvath*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1162 Citations (Scopus)

Abstract

It was unknown whether plasma protein levels can be estimated based on DNA methylation (DNAm) levels, and if so, how the resulting surrogates can be consolidated into a powerful predictor of lifespan. We present here, seven DNAm-based estimators of plasma proteins including those of plasminogen activator inhibitor 1 (PAI-1) and growth differentiation factor 15. The resulting predictor of lifespan, DNAm GrimAge (in units of years), is a composite biomarker based on the seven DNAm surrogates and a DNAm-based estimator of smoking packyears. Adjusting DNAm GrimAge for chronological age generated novel measure of epigenetic age acceleration, AgeAccelGrim. Using large scale validation data from thousands of individuals, we demonstrate that DNAm GrimAge stands out among existing epigenetic clocks in terms of its predictive ability for time-to-death (Cox regression P=2.0E- 75), time-to-coronary heart disease (P=6.2E-24), time-to-cancer (P= 1.3E-12), its strong relationship with computed tomography data for fatty liver/excess visceral fat, and age-at-menopause (P=1.6E-12). AgeAccelGrim is strongly associated with a host of age-related conditions including comorbidity count (P=3.45E- 17). Similarly, age-adjusted DNAm PAI-1 levels are associated with lifespan (P=5.4E-28), comorbidity count (P= 7.3E-56) and type 2 diabetes (P=2.0E-26). These DNAm-based biomarkers show the expected relationship with lifestyle factors including healthy diet and educational attainment. Overall, these epigenetic biomarkers are expected to find many applications including human anti-aging studies.

Original languageEnglish
Pages (from-to)303-327
Number of pages25
JournalAging
Volume11
Issue number2
DOIs
Publication statusPublished - 1 Jan 2019

Bibliographical note

Publisher Copyright:
© 2019, Lu et al.

Keywords

  • DNA methylation
  • Epigenetics
  • Mortality
  • Proteomics

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